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THE VIDEO SHELF · category theory

Category Theory in Life - Eugenia Cheng

Eugenia Cheng gives the opening keynote at Lambda World 2017, presenting category theory as very abstract algebra whose abstraction gives it broad applicability. She applies it to everyday questions including privilege and prejudice.

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Why HN readers recommended it

HN recommends it as an accessible, gentle introduction that makes category theory feel approachable and shows its analogy-making power.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Lambda World
Topic
category theory
Format
talk
Level
intro
HN recommenders in dataset
3
HN mentions in dataset
3
Recommendation years in dataset
2019–2022

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • "But it’s hard to explain to people not steeped in the subject." I don't agree. Actually it can be understood relatively easily, if it's explained well: [VIDEO] [LINK]

    sunmao on Hacker News · 2019-04
    In How category theory is applied

  • There is an applied category theory course that is currently in the process of wrapping up: [LINK] The examples in the course offer a complementary entry point to category theory compared to an approach that leverages programmers' knowledge of functional programming. Personally, the more examples …

    gugagore on Hacker News · 2021-02
    In What Is Applied Category Theory? (2018)

  • Eugenia Cheng has some interesting and accessible videos, e.g.: [VIDEO] and in a similar vein I am enjoying her book: "How to Bake Pi". Getting more into the technical side of things, Bartosz Milewski has good lessons in this playlist: [LINK]

    OracB7 on Hacker News · 2022-08
    In How to learn hard things in tech

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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